Rowhammer is a disturbance error in Dynamic Random-Access Memory (DRAM) that can be deliberately triggered from software by repeatedly reading, i. e., hammering, proximate memory locations in different DRAM rows. While numerous studies evaluated the Rowhammer effect, in particular how it can be triggered and how it can be exploited, most studies only use a small sample size of Dual In-line Memory Modules (DIMMs). Only few studies provided indication for the prevalence of the effect, with clear limitations to specific hardware configurations or FPGA-based experiments with precise control of the DIMM, limiting how far the results can be generalized.

In this paper, we perform the frist large-scale study of the Rowhammer effect involving 1 006 data sets from 822 systems. We measure Rowhammer prevalence in a fully automated crossplatform framework, FLIPKIT, using the available state-of-theart software-based DRAM and Rowhammer tools. Our framework automatically gathers information about the DRAM and uses 5 tools to reverse-engineer the DRAM addressing functions, and based on the reverse-engineered functions uses 7 tools to mount Rowhammer. We distributed the framework online and via USB thumb drives to thousands of participants from December 30, 2024, to June 30, 2025. Overall, we collected 1 006 datasets from systems with various CPUs, DRAM generations, and vendors. Our study reveals that out of 1 006 datasets, 453 (371 of the 822 unique systems) succeeded in the first stage of reverseengineering the DRAM addressing functions, indicating that successfully and reliably recovering DRAM addressing functions remains a significant open problem. In the second stage, 126 (12.5 % of all datasets) exhibited bit flips in our fully automated Rowhammer attacks. Our results show that fully-automated, i. e., weaponizable, Rowhammer attacks work on a lower share of systems than FPGA-based and lab experiments indicated but with 12.5 % enough to be a practical vector for threat actors. Furthermore, our results highlight that the two most pressing research challenges around Rowhammer exploitability are more reliable reverse-engineering addressing functions, as 50 % of datasets without bit flips failed in the DRAM reverse-engineering stage, and reliable Rowhammer attacks across diverse processor microarchitectures1, as only 12.5 % of datasets contained bit flips. Addressing each of these challenges could double the number of systems susceptible to Rowhammer and make Rowhammer a more pressing threat in real-world scenarios. 

This paper introduces StoryMachine (AHRC grant ref. AH/Z507222/1, DFG project number 547532269), a newly funded transdisciplinary project (2025-2028) conducted jointly by six research groups in Germany and the UK, which aims to develop an innovative digital infrastructure to preserve, explore, and democratize access to folklore traditions and vernacular storytelling practices around the world, with a particular focus on German- and English-speaking communities. Recognizing folklore as a cornerstone of shared cultural identity, the project addresses critical challenges in archival practices, and in particular the lack of interactive, dynamic, accessible and inclusive tools for exploring both traditional and emerging folk narratives. Existing approaches to digital folklore archiving remain largely static, focusing on isolated collections without fostering meaningful exploration, collaboration, or analysis. StoryMachine redefines these paradigms by integrating spatial hypertext and recommender systems to create a visually dynamic, user-centered interface.

The transdisciplinary Digital Humanities project StoryMachine, conducted jointly (2025–2028) by six research groups in Germany and the UK, is developing an innovative digital infrastructure to preserve, explore, and democratize access to folklore traditions and vernacular storytelling practices around the world, with emphasis on German- and English-speaking communities. Recognizing folklore as a cornerstone of shared cultural identity, the project addresses critical challenges in archival practices, and particularly the lack of interactive, dynamic, accessible and inclusive tools for exploring both traditional and emerging folk narratives. Existing approaches to digital folklore archiving remain largely static, focusing on isolated collections without fostering meaningful exploration, collaboration, or analysis. StoryMachine redefines these paradigms by integrating spatial hypertext and recommender systems to create a visually dynamic, user-centered interface, which empowers users to actively participate in ongoing transregional, transcultural narrative practices while expanding previously dominant linear forms of storytelling to reflect the diversity and multifaceted nature of contemporary folklore.

The digital product passport is becoming an essential tool to increase transparency about the sustainability of products and to boost the circular economy in the European Union. With the revised Ecodesign for Sustainable Products Regulation having entered into force in July 2024, the digital product passport will become a necessary extension for many products placed on the European market. Industry practitioners are faced with the challenge of fulfilling content requirements while maintaining interoperability at the same time. Although industry practitioners face challenges in implementing digital product passports, existing research has largely focused on digital product passport systems, often overlooking the crucial aspect of digital product passport data. Work on this data typically falls short of addressing comprehensive interoperability. This research therefore proposes a minimal digital product passport data model that integrates current regulatory requirements while ensuring interoperability through the use of standardised submodel templates of the asset administration shell. We demonstrate that the current regulatory requirements can be met, but foreseeable extensions will require adjustments and therefore close synchronisation between standardisation initiatives and the institutions that further specify regulatory requirements.

Selected Contributions: Sustainable Excellence—Economic, Social, and Environmental Issues presents a curated collection of peer-reviewed research papers presented at the 2nd Tunisian Symposium on Economics and Management (TSEM 2025), held in Tunisia from April 11 to 13, 2025. The symposium was organised by the Research Unit "Economy, Enterprise, Environment" (3E) at the Higher Institute of Management (ISG), University of Gabes.

This volume offers a multidisciplinary and innovative examination of the factors underpinning sustainable excellence amid contemporary global challenges. The contributions are organised around five core themes: first, the role of innovation as a critical driver of ecological transition; second, the transformation of labour markets and accompanying social dynamics necessary for a just transition; third, the design and evaluation of sustainable economic models; fourth, the synergistic effects of artificial intelligence (AI) and financial inclusion on progress toward the Sustainable Development Goals (SDGs); and fifth, the significance of responsible managerial practices grounded in corporate social responsibility (CSR) and ethical governance.

Collectively, these contributions provide rigorous, timely insights into the interdependencies among economic, social, and environmental systems. This volume serves as an essential reference for academics, researchers, policymakers, and practitioners in the field.

The new Ecodesign for Sustainable Products Regulation (EU) 2024/1781 (ESPR) establishes a comprehensive legal framework within the EU that aims to make sustainable products the norm. It introduces measures such as ecodesign requirements, digital product passports, and physical labels, with the intention of encouraging sustainable choices and market surveillance. Textiles are among the first product groups to be targeted with these requirements due to their environmental impact, and an ongoing preparatory study is being conducted by the Joint Research Centre (JRC). This study at hand was commissioned by the German Environment Agency (UBA) and was conducted by the Oeko-Institut in collaboration with two universities of
applied sciences: the Hochschule Niederrhein and the Hochschule Hof. The study aims to support the development of ecodesign requirements for textiles and to explore how these requirements can be communicated effectively through an ecodesign label.

The study’s methodology included literature review, expert consultation, market analysis, and stakeholder workshops. The developed requirements relate to durability, repairability, recyclability, recycled content, and substances of concern. Three product examples were in the focus of the study: T-shirts, jeans and functional jackets.

This paper investigates the physiological responses of individuals driving both on a real
route and within a vehicle simulator designed as a digital twin of that route. The analysis
of observed data patterns in stress response bio signals provides sufficient evidence of
similarity to validating the driving simulation digital twin as a reliable replacement for
real-world experiences in controlled and consistent settings, or when overall trends of
physiological variables, rather than specific variable levels, are of interest. The findings also
stress the need for optimizing the precision of digital twins in complex settings. This study
introduces a time-series-based validation approach for driving digital twins by comparing
continuous physiological trajectories between real and simulated driving

Successful innovation processes involve multiple actors with distinct objectives, resources,
and competences across different stages of value creation. Close collaboration among relevant
stakeholders is therefore essential, yet it also entails substantial coordination and alignment
challenges. Drawing on a multi-method research design, this study examines the development and
market introduction of an advanced driver assistance system (ADAS) for passenger vehicles across
multiple market stages.
The findings conceptually and empirically demonstrate how stakeholders’ heterogeneous goal
structures and value assessments influence the innovation process across stages. In particular, the
results reveal that the absence of a multi-stage marketing (MSM) perspective can lead to
misalignments that adversely affect the progression and market success of the innovation. The
study further provides insights into how innovation processes can be systematically designed
across market stages to ensure end-user orientation and economic viability.
By integrating a multi-stage marketing perspective into innovation research, this paper
contributes to a more comprehensive understanding of innovation processes in complex, multi-
actor environments.

At a time when vehicle automation is becoming increasingly important, there
is a growing need for greater consumer centricity. However, the importance of
effectively deriving functional product specifications appears to be diminishing.
The case of Automated Parking Systems (APS) demonstrates that the automotive
industry often employs a top-down approach, in contrast to a more customer-
-centric method in the development process. To assess the effectiveness of this
top-down approach, we conducted a field study and a mixed-method online
survey to explore user expectations of APS functionality. Our findings indicate
that drivers strongly dislike excessive parking maneuvers caused by overly re-
strictive product specifications. Moreover, user demands are less stringent
than the development requirements set by OEMs. Based on these insights, we
recommend adopting a more user-centered approach. This shift could enable
companies to reduce development costs and time investments, while accelerat-
ing the adoption of their innovations.

Scents influence emotions, cognition and behavior by activating memories, enhanc-
ing mood and modulating mental processes. Perception of scents is shaped by both
stimulus-related dimensions, including familiarity, pleasantness and intensity and
individual factors – such as mood, sensory sensitivity and personality traits. The
present study systematically examined the relative impact of these determinants in
a quasi-experimental design involving 51 participants. Seven scents were evaluated
along perceptual dimensions (recognizability, pleasantness, familiarity, intensity)
and related to participants’ individual characteristics. Findings emphasize the inter-
play of stimulus-related dimensions and personality traits but highlight the need
for refined measures of (sensory-specific) personality traits in olfactory process-
ing for multisensory marketing and immersive applications.

Für die Organisation von Inhalten und Informationen, als Lernumgebung und zur Strukturierung von Wissen ist es schon länger DIE Killer-Applikation – NotebookLM. Jetzt kann man mit dem kostenlosen Google-Tool auch zusätzliche Formate wie Lern- und Erklärvideos auf Knopfdruck erstellen.

Der Einsatz von Blockchain und Smart Contracts ermöglicht auch den Aufbau und Betrieb dezentraler autonomer Organisationen, sogenannter DAOs, die auf Grundlage eines zuvor fixierten Regelsystems automatisiert Entscheidungen treffen und an den Märkten als eigenständige Institution agieren können. Während DAOs in anderen Bereichen – in der Finanzwirtschaft und in der Creator-Economy – bereits regelmäßig zum Einsatz kommen, ist im industriellen Umfeld eine entsprechende Nutzbarmachung bislang kaum zu verzeichnen. Dabei bietet gerade die Vernetzung durch das „Internet der Dinge“ hierfür sinnvolle Anknüpfungspunkte. Der Beitrag befasst sich mit den möglichen wirtschaftlichen Adaptionsansätzen und lotet potenzielle Geschäftsmodelle aus, die sich aus der Errichtung von DAOs in der „Industrie 4.0“ ergeben könnten.